code: def configure_optimizers(self):
      optimizer = nni.trace(torch.optim.SGD)(
          self.parameters(),
          lr=0.01,
          momentum=0.9,
          weight_decay=5e-4,
      )
      scheduler_dict = {
          "scheduler": nni.trace(ExponentialLR)(
              optimizer,
              0.1,
          ),
          "interval": "epoch",
      }
      return {"optimizer": optimizer, "lr_scheduler": scheduler_dict}
  
imports: from __future__ import annotations
  import pytorch_lightning
  import torch
  import torch.nn.functional
  from torch.optim.lr_scheduler import ExponentialLR
  from torch.utils.data import random_split, DataLoader
  from torchmetrics.functional import accuracy
  from torchvision.datasets import MNIST
  from torchvision import transforms
  import nni
  from .simple_torch_model import SimpleTorchModel
label_desc: Use image node_id 7 for calling the SimpleLightningModel obj's underlying member method code with example usage: obj.configure_optimizers() and returns: dict